Patel Dhilon S, Bharatam Prasad V
Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research, S.A.S. Nagar, Mohali 160 062, Punjab, India.
Eur J Med Chem. 2008 May;43(5):949-57. doi: 10.1016/j.ejmech.2007.06.016. Epub 2007 Jul 10.
In the development of drugs targeted for GSK-3, its selective inhibition is an important requirement owing to the possibility of side effects arising from other kinases for the treatment of diabetes mellitus. A three-dimensional quantitative structure-activity relationship study (3D-QSAR) has been carried out on a set of pyrazolo[3,4-b]pyrid[az]ine derivatives, which includes non-selective and selective GSK-3 inhibitors. The CoMFA models were derived from a training set of 59 molecules. A test set containing 14 molecules (not used in model generation) was used to validate the CoMFA models. The best CoMFA model generated by applying leave-one-out (LOO) cross-validation study gave cross-validation r(cv)(2) and conventional r(conv)(2) values of 0.60 and 0.97, respectively, and r(pred)(2) value of 0.55, which provide the predictive ability of model. The developed models well explain (i) the observed variance in the activity and (ii) structural difference between the selective and non-selective GSK-3 inhibitors. Validation based on the molecular docking has also been carried out to explain the structural differences between the selective and non-selective molecules in the given series of molecules.
在开发针对糖原合成酶激酶-3(GSK-3)的药物时,由于治疗糖尿病时其他激酶可能产生副作用,其选择性抑制是一项重要要求。已对一组吡唑并[3,4-b]吡啶嗪衍生物进行了三维定量构效关系研究(3D-QSAR),其中包括非选择性和选择性GSK-3抑制剂。比较分子场分析(CoMFA)模型源自59个分子的训练集。使用包含14个分子的测试集(未用于模型生成)来验证CoMFA模型。通过留一法(LOO)交叉验证研究生成的最佳CoMFA模型的交叉验证r(cv)(2)和常规r(conv)(2)值分别为0.60和0.97,r(pred)(2)值为0.55,这提供了模型的预测能力。所开发的模型很好地解释了(i)观察到的活性差异以及(ii)选择性和非选择性GSK-3抑制剂之间的结构差异。还基于分子对接进行了验证,以解释给定系列分子中选择性和非选择性分子之间的结构差异。